{"id":8,"date":"2021-06-24T18:14:14","date_gmt":"2021-06-24T18:14:14","guid":{"rendered":"https:\/\/www.isi.edu\/ai\/?page_id=8"},"modified":"2025-06-05T17:13:34","modified_gmt":"2025-06-05T17:13:34","slug":"research-areas","status":"publish","type":"page","link":"https:\/\/www.isi.edu\/ai\/research-areas\/","title":{"rendered":"Research Areas"},"content":{"rendered":"\n\n\t<a onclick=\"topFunction()\" id=\"toTop\" aria-label=\"Go to top\">\n<\/a>\n<p>The division conducts fundamental and applied research in the following topics:<\/p>\n<header>\n<h2>Areas of Research<\/h2>\n<ul>\n<li><a href=\"#mla\">Machine Learning and Applications<\/a><\/li>\n<li><a href=\"#nlp\">Natural Language Processing<\/a><\/li>\n<li><a href=\"#kg\">Knowledge Graphs<\/a><\/li>\n<li><a href=\"#sdad\">Scientific Data Analysis and Discovery<\/a><\/li>\n<li><a href=\"#mmu\">Multi-modal Understanding<\/a><\/li>\n<li><a href=\"#csrr\">Common Sense Representation and Reasoning<\/a><\/li>\n<li><a href=\"#css\">Computational Social Science<\/a><\/li>\n<li><a href=\"#ai-safety\">AI Robustness and Safety<\/a><\/li>\n<\/ul>\n<\/header>\n<article>\n    <section><h2>Machine Learning and Applications<\/h2><p>Focusing on fundamental research, including AI robustness, adversarial machine learning, anti-spoofing, domain adaptation and federated learning, and applied research in application areas such as biomedical sciences, biometric authentication, computational social science and cybersecurity.\u00a0<h3>People<\/h3>Wael Abd-Almageed &#8211; <a href=\"https:\/\/www.isi.edu\/directory\/ambite\/\" target=\"_blank\" rel=\"noopener\">Jose Luis Ambite<\/a> &#8211; <a href=\"https:\/\/www.isi.edu\/directory\/galstyan\/\" target=\"_blank\" rel=\"noopener\">Aram Galstyan<\/a> &#8211; <a href=\"https:\/\/www.isi.edu\/directory\/shri\/\" target=\"_blank\" rel=\"noopener\">Shrikanth Narayanan<\/a> &#8211; <a href=\"https:\/\/www.isi.edu\/directory\/jpujara\/\" target=\"_blank\" rel=\"noopener\">Jay Pujara<\/a> &#8211; <a href=\"https:\/\/www.isi.edu\/directory\/ilievski\/\" target=\"_blank\" rel=\"noopener\">Filip Ilievski<\/a> &#8211; <a href=\"https:\/\/www.isi.edu\/directory\/muhao\/\" target=\"_blank\" rel=\"noopener\">Muhao Chen<\/a>\u00a0&#8211; <a href=\"https:\/\/www.isi.edu\/directory\/xuezhema\/\" target=\"_blank\" rel=\"noopener\">Xuezhe Ma<\/a> &#8211; <a href=\"https:\/\/www.isi.edu\/directory\/gregv\/\" target=\"_blank\" rel=\"noopener\">Greg Ver Steeg<\/a> &#8211; <a href=\"https:\/\/www.isi.edu\/directory\/kyao\/\" target=\"_blank\" rel=\"noopener\">Ke-Thia Yao<\/a> &#8211; <a href=\"http:\/\/isi.edu\/directory\/mrostami\/\" target=\"_blank\" rel=\"noopener\">Mohammad Rostami<\/a><\/p><h3>Projects<\/h3><ul><li><a href=\"https:\/\/usc-isi-i2.github.io\/mowgli\/\">Commonsense reasoning <\/a><br \/>Multi-modal open world grounded learning and inference<\/li><li><strong>CORAL<\/strong><br \/>Combined Representations for Adept Learning (DARPA Learning with Less Labels)<\/li><li><strong>QUASAR<\/strong><br \/>QUantum Assisted Sampling for MAchine LeaRning (DARPA)<\/li><li><strong>Secure Heterogeneous Learning Federation with Information\u2011Theoretic Guarantees (DARPA)<\/strong><\/li><li><strong>BATL<\/strong><br \/>Biometrics Authentication with a Timeless Learner (IARPA)<\/li><li><strong>LR2<\/strong><br \/>Learning Robust Representations (DARPA)<\/li><li><strong>AI2AI<\/strong><br \/>AI Investigating AI (Keston Award)<\/li><li><strong>DARPA Cooperative Secure Learning SHELFI<\/strong><br \/>Secure Heterogeneous Learning Federation with Information-Theoretic Guarantees<\/li><\/ul><\/section>\n    <section><img decoding=\"async\" loading=\"lazy\" src=\"https:\/\/www.isi.edu\/ai\/wp-content\/uploads\/sites\/6\/2021\/07\/mt-usc.jpg\" alt=\"robot hand touching computer keyboard\"\/><\/section>\n<\/article>\n<article>\n    <section><img decoding=\"async\" loading=\"lazy\" src=\"https:\/\/www.isi.edu\/ai\/wp-content\/uploads\/sites\/6\/2021\/07\/nl-usc.jpg\" alt=\"human and robot profiles face to face\"\/><\/section>\n    <section><h2>Natural Language Processing<\/h2><p>Focusing on low resource machine translation, multilingual representation learning, transfer learning, dialogue, decision-making, question answering, summarization, ontologies, information retrieval, text decipherment.<br \/><a href=\"https:\/\/www.isi.edu\/research_groups\/nlg\/home\">Visit Website<\/a><h3>People<\/h3><a href=\"https:\/\/www.isi.edu\/directory\/jonmay\/\" target=\"_blank\" rel=\"noopener\">Jon May<\/a> &#8211; <a href=\"https:\/\/www.isi.edu\/directory\/muhao\/\" target=\"_blank\" rel=\"noopener\">Muhao Chen<\/a> &#8211; <a href=\"https:\/\/www.isi.edu\/directory\/xuezhema\/\" target=\"_blank\" rel=\"noopener\">Xuezhe Ma<\/a> &#8211; <a href=\"https:\/\/www.isi.edu\/directory\/xiangren\/\" target=\"_blank\" rel=\"noopener\">Xiang Ren<\/a> &#8211; <a href=\"https:\/\/www.isi.edu\/directory\/ulf\/\" target=\"_blank\" rel=\"noopener\">Ulf Hermjakob<\/a> &#8211; Elizabeth Boschee &#8211; <a href=\"https:\/\/www.isi.edu\/directory\/mrf\/\" target=\"_blank\" rel=\"noopener\">Marjorie Freedman<\/a> &#8211; <a href=\"https:\/\/www.isi.edu\/directory\/hobbs\/\" target=\"_blank\" rel=\"noopener\">Jerry Hobbs<\/a> &#8211; <a href=\"https:\/\/www.isi.edu\/directory\/smiller\/\" target=\"_blank\" rel=\"noopener\">Scott Miller <\/a>&#8211; <a href=\"https:\/\/vnpeng.net\/\" target=\"_blank\" rel=\"noopener\">Nanyun (Violet) Peng<\/a>\u00a0<\/p><h3>Projects<\/h3><ul><li><strong>CLEAR<\/strong><br \/>Cross-Lingual Event and Argument Retrieval (IARPA BETTER)<\/li><li><strong>CORAL<\/strong><br \/>Combined Representations for Adept Learning (DARPA Learning with Less Labels)<\/li><li><strong>ELICIT<\/strong><br \/>A System for Extracting and Organizing Causal Information (DARPA Causal Exploration)<\/li><li><strong>ELISA<\/strong><br \/>Exploiting Language Information for Situational Awareness (DARPA LORELEI)<\/li><li aria-level=\"1\"><strong>EvidxExtraction<\/strong><br \/>Evidence Extraction Systems for the Molecular Interaction Literature (NIH R01)<\/li><li><strong>LESTAT<\/strong><br \/>Learning Event Schema Temporally and Transmodally (DARPA KAIROS)<\/li><li><strong>MICS<\/strong><br \/>Machine Intelligence from Common Sense (DARPA MCS)<\/li><li aria-level=\"1\"><strong>SARAL<\/strong><br \/>Summarization and Domain-Adaptive Retrieval Across Languages (IARPA MATERIAL)<\/li><\/ul><\/section>\n<\/article>\n<article>\n    <section><h2>Knowledge Graphs<\/h2><p>Using AI and machine learning techniques to construct and exploit large-scale knowledge bases and to induce taxonomies from data. Notable applications include probabilistic models for scientific reproducibility, incorporating extractions from scientific articles and scientific networks of citation and reference, and business knowledge graphs characterizing innovation and competition using web data and regulatory filings.<br \/><a href=\"\/centers-ckg\/\">Visit Website<\/a><h3>People<\/h3><a href=\"https:\/\/www.isi.edu\/directory\/jpujara\/\" target=\"_blank\" rel=\"noopener\">Jay Pujara<\/a> &#8211; <a href=\"https:\/\/www.isi.edu\/directory\/ilievski\/\" target=\"_blank\" rel=\"noopener\">Filip Ilievski<\/a> &#8211; <a href=\"https:\/\/www.isi.edu\/directory\/kyao\/\" target=\"_blank\" rel=\"noopener\">Ke-Thia Yao<\/a> &#8211; <a href=\"https:\/\/www.isi.edu\/directory\/muhao\/\" target=\"_blank\" rel=\"noopener\">Muhao Chen<\/a> &#8211; <a href=\"https:\/\/www.isi.edu\/directory\/knoblock\/\" target=\"_blank\" rel=\"noopener\">Craig Knoblock\u00a0<\/a>&#8211; <a href=\"https:\/\/www.isi.edu\/directory\/ambite\/\" target=\"_blank\" rel=\"noopener\">Jose Luis Ambite<\/a><\/p><h3>Projects<\/h3><ul><li><a href=\"https:\/\/usc-isi-i2.github.io\/kgtk\/\">KGTK<\/a><br \/>The Knowledge Graph Toolkit (DARPA)<\/li><li><strong>Table Linker<\/strong><br \/>Linking tables to knowledge graphs (DARPA, Novartis)<\/li><li><strong>Building a knowledge graph for food security (DARPA)<\/strong><\/li><li><a href=\"https:\/\/usc-isi-i2.github.io\/datamart\/\">Datamart<\/a><br \/>Creating the largest publicly available knowledge graph to power data-driven models (DARPA)<\/li><li><a href=\"https:\/\/usc-isi-i2.github.io\/karma\/\">Karma<\/a><br \/>A data integration tool<\/li><li><a href=\"https:\/\/usc-isi-i2.github.io\/bokn\/\">Knowledge graphs for business (DARPA)<\/a><\/li><li><a href=\"https:\/\/usc-isi-i2.github.io\/macro-score\/\">Scoring scientific research<\/a><br \/>Developing automated techniques for evaluating scientific claims (DARPA)<\/li><li><a href=\"https:\/\/usc-isi-i2.github.io\/semantic-modeling\/\">Semantic modeling<\/a><br \/>Automatically building semantic models of sources (DARPA)<\/li><li><strong>CSKG<\/strong><br \/>The commonsense knowledge graph<\/li><li aria-level=\"1\"><a href=\"https:\/\/www.nsf.gov\/awardsearch\/showAward?AWD_ID=2105329&amp;HistoricalAwards=false\"><strong>Knowledge Graph Completion with Transferable Representation Learning (NSF)<\/strong><\/a><\/li><li><strong>Novartis-USC<\/strong><br \/>Scaling Up Data FAIR-ificaton<\/li><\/ul><\/section>\n    <section><img decoding=\"async\" loading=\"lazy\" src=\"https:\/\/www.isi.edu\/ai\/wp-content\/uploads\/sites\/6\/2021\/07\/ckg-usc.jpg\" alt=\"colored shapes connected by lines\"\/><\/section>\n<\/article>\n<article>\n    <section><img decoding=\"async\" loading=\"lazy\" src=\"https:\/\/www.isi.edu\/ai\/wp-content\/uploads\/sites\/6\/2021\/07\/KCD-Graphics.png\" alt=\"complex charts\"\/><\/section>\n    <section><h2>Scientific Data Analysis and Discovery<\/h2>\nUsing interactive knowledge capture, intelligent user interfaces, semantic workflows, provenance, and collaboration; large-scale data integration and analysis of biomedical data (including sensor, environmental, neuroimaging, clinical and genetic data) and (paleo)climate data.<br \/>\n<a href=\"https:\/\/knowledgecaptureanddiscovery.github.io\">Visit Website<\/a>\n<h3>People<\/h3>\n<p><a href=\"https:\/\/www.isi.edu\/directory\/gil\/\" target=\"_blank\" rel=\"noopener\">Yolanda Gil<\/a> &#8211; <a href=\"https:\/\/www.isi.edu\/directory\/dkhider\/\" target=\"_blank\" rel=\"noopener\">Deborah Khider<\/a> &#8211; <a href=\"https:\/\/www.isi.edu\/directory\/ambite\/\" target=\"_blank\" rel=\"noopener\">Jose Luis Ambite<\/a><\/p>\n<h3>Projects<\/h3>\n<ul>\n<li><a href=\"https:\/\/www.wings-workflows.org\">WINGS<\/a><br \/>\nA semantic workflow system that assists scientists with the design of computational experiments<\/li>\n<li><a href=\"http:\/\/mint-project.info\/\">MINT<\/a><br \/>\nIntegrating scientific models<\/li>\n<li><a href=\"https:\/\/disk-project.org\">DISK<\/a><br \/>\nAutomating the discovery of scientific models<\/li>\n<li><a href=\"https:\/\/linkedearth.github.io\/\">LinkedEarth<\/a><br \/>\nPaleoclimate data and analysis\n<ul>\n<li><a href=\"https:\/\/knowledgecaptureanddiscovery.github.io\/autoTS\/\">autoTS<\/a><br \/>\nAutomating time series analysis<\/li>\n<li><a href=\"https:\/\/paleopresto.github.io\">PreSto<\/a><br \/>\nPaleoclimate Reconstruction Storehouse<\/li>\n<\/ul>\n<\/li>\n<li><a href=\"https:\/\/scientificpaperofthefuture.org\">Scientific\/geoscience paper of the future<\/a><br \/>\nEncouraging scientists to publish papers with the associated products of their research<\/li>\n<li><strong><a href=\"https:\/\/zenodo.org\/record\/1251321#.YTeQwi1h30o\">P4ML<\/a><\/strong><br \/>\nA phased performance-based pipeline planner for automated machine learning<\/li>\n<li><strong>ASSET<\/strong><br \/>\nA sketching project to accelerate scientific workflows<\/li>\n<li><strong><a href=\"https:\/\/ontosoft.org\">OntoSoft<\/a><\/strong><br \/>\nA software metadata registry to describe scientific software in a user-friendly manner<\/li>\n<li><strong><a href=\"http:\/\/www.organicdatascience.org\">Organic data science<\/a><\/strong><br \/>\nResolving science processes through an open framework that facilitates participation<\/li>\n<li><strong><a href=\"https:\/\/www.opmw.org\">OPMW-Prov<\/a><\/strong><br \/>\nTracking the provenance of scientific experiments and their executions<\/li>\n<li><a href=\"http:\/\/www.genome.gov\/\">NHGRI<\/a><br \/>\nNational Human Genome Research Institute\n<ul>\n<li><a href=\"http:\/\/www.pagestudy.org\/\">PAGE<\/a><br \/>\nPopulation Architecture using Genomics and Epidemiology Coordinating Center<\/li>\n<\/ul>\n<\/li>\n<li><b>NeuroBridge<\/b><br \/>\nAutomating the discovery of scientific models<\/li>\n<li><a href=\"https:\/\/www.nimh.nih.gov\/\">NIMH<\/a><br \/>\nNational Institute of Mental Health\n<ul>\n<li><a href=\"http:\/\/www.nimhgenetics.org\/\">NRGR<\/a><br \/>\nRepository and Genomics Resource<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<\/section>\n<\/article>\n<article>\n    <section><h2>Multi-modal Understanding<\/h2><p>Including image and video understanding for deepfake detection, visual misinformation identification, identifying manipulated scientific literature and multimedia analysis, face recognition, biometric anti-spoofing, and robust AI; table understanding to automate exploitation of millions of tables on the web focusing on automatic layout detection, semantic modeling, table retrieval, table summarization, entity linking, and fact-checking. <h3>People<\/h3>Wael Abd-Almageed &#8211; <a href=\"https:\/\/www.isi.edu\/directory\/jpujara\/\" target=\"_blank\" rel=\"noopener\">Jay Pujara<\/a>\u00a0&#8211; <a href=\"https:\/\/www.isi.edu\/directory\/muhao\/\" target=\"_blank\" rel=\"noopener\">Muhao Chen<\/a><\/p><h3>Projects<\/h3><ul><li><a href=\"https:\/\/usc-isi-i2.github.io\/Timeseries\/\">Table Understanding<\/a><br \/>Understanding the structure and semantics of tables (DARPA)<\/li><li><strong>DiSPARITY<\/strong><br \/>Digital, Semantic and Physical Analysis of media integRITY (DARPA)<\/li><\/ul><\/section>\n    <section><img decoding=\"async\" loading=\"lazy\" src=\"https:\/\/www.isi.edu\/ai\/wp-content\/uploads\/sites\/6\/2021\/09\/aimu_isi.jpg\" alt=\"profiles of person to person talking\"\/><\/section>\n<\/article>\n<article>\n    <section><img decoding=\"async\" loading=\"lazy\" src=\"https:\/\/www.isi.edu\/ai\/wp-content\/uploads\/sites\/6\/2021\/07\/aicsrr-isi.jpg\" alt=\"profile of person with objects coming out of their head\"\/><\/section>\n    <section><h2>Common Sense Representation and Reasoning<\/h2>\nUsing cognitively-inspired computational paradigms for evaluating commonsense AI (including those based on large-scale language models) to create and solve new challenge tasks based on logical axioms and numeracy; \u00a0 human-centric dialog agents that maximize metrics of human utility alongside algorithmic utility in task-focused dialogs; game-theoretic simulators for poker, Monopoly, and wargames that enable refinement and evaluation of theories of novelty for general AI agents.<br \/>\n<a href=\"https:\/\/usc-isi-i2.github.io\/mowgli\/\">Visit Website<\/a>\n<h3>People<\/h3>\n<p><a href=\"https:\/\/www.isi.edu\/directory\/kejriwal\/\" target=\"_blank\" rel=\"noopener\">Mayank Kejriwal<\/a>\u00a0&#8211; <a href=\"https:\/\/www.isi.edu\/directory\/jpujara\/\" target=\"_blank\" rel=\"noopener\">Jay Pujara<\/a> &#8211; <a href=\"https:\/\/www.isi.edu\/directory\/ilievski\/\" target=\"_blank\" rel=\"noopener\">Filip Ilievski<\/a> &#8211; <a href=\"https:\/\/www.isi.edu\/directory\/muhao\/\" target=\"_blank\" rel=\"noopener\">Muhao Chen<\/a> &#8211; <a href=\"https:\/\/www.isi.edu\/directory\/xiangren\/\" target=\"_blank\" rel=\"noopener\">Xiang Ren<\/a><\/p>\n<h3>Projects<\/h3>\n<ul>\n<li><a href=\"https:\/\/usc-isi-i2.github.io\/mowgli\/\">Commonsense reasoning<\/a><br \/>\nMulti-modal open world grounded learning and inference<\/li>\n<li><strong>CSKG<\/strong><br \/>\nThe commonsense knowledge graph<\/li>\n<\/ul>\n<\/section>\n<\/article>\n<article>\n    <section><h2>Computational Social Science<\/h2><p>With emphasis on structure detection and pattern matching in unusual complex systems with hidden information (e.g., human trafficking, dark money networks); large-scale, contextualized social media analysis (e.g., in the context of natural disasters) including analysis involving non-verbal tokens such as emojis; computational social science methods for quantifying socio-demographically segmented impacts of COVID-19 on wellbeing, technological inequity, and vaccine hesitancy; applied AI in industrial applications, such as e-commerce.<h3>People<\/h3><a href=\"https:\/\/www.isi.edu\/directory\/ferrarae\/\" target=\"_blank\" rel=\"noopener\">Emilio Ferrara<\/a> &#8211; <a href=\"https:\/\/www.isi.edu\/directory\/lerman\/\" target=\"_blank\" rel=\"noopener\">Kristina Lerman<\/a> &#8211; <a href=\"http:\/\/isi.edu\/directory\/fredmors\/\" target=\"_blank\" rel=\"noopener\">Fred Morstatter<\/a> &#8211; <a href=\"https:\/\/www.isi.edu\/directory\/gmuric\/\" target=\"_blank\" rel=\"noopener\">Goran Muric<\/a> &#8211; Keith Burghardt<\/p><h3>Projects<\/h3><ul><li><strong>Polarization in the context of COVID-19<\/strong><br \/>The pandemic has exacerbated echo chambers, paving the way for the rampant spread of misinformation.<\/li><li aria-level=\"1\"><strong>Science of growth<br \/><\/strong>This project explores the impact of growth on various human behaviors, such as how the growth of cities impact infrastructure, how message boards increase interactions, or the growth of institutions impact collaborations.<\/li><li aria-level=\"1\"><strong>DARPA Influence Campaign Awareness and Sensemaking (INCAS)<\/strong><ul><li aria-level=\"2\"><strong>Early Detection of Influence Indicators with Machine Intelligence (EDIFICE)<\/strong><br \/>Project to detect influence campaigns in foreign social media<\/li><li aria-level=\"2\"><strong>Universal Population Segmentation and Characterization Algorithms for OnLine Environments (UPSCALE)<\/strong><br \/>Project to analyze influence campaigns in foreign social media<\/li><\/ul><\/li><li aria-level=\"1\"><strong>VENICE<\/strong><br \/>VErifyiNg Implicit Cultural modEls: Infer cultural causal relationships; store in queryable knowledge graph. Verify relationships via real-world interviews with people in foreign country.<\/li><\/ul><\/section>\n    <section><img decoding=\"async\" loading=\"lazy\" src=\"https:\/\/www.isi.edu\/ai\/wp-content\/uploads\/sites\/6\/2021\/07\/aicss-isi.jpg\" alt=\"Dark human shadow in front of convoluted pink figure\"\/><\/section>\n<\/article>\n<article>\n    <section><img decoding=\"async\" loading=\"lazy\" src=\"https:\/\/www.isi.edu\/ai\/wp-content\/uploads\/sites\/6\/2021\/07\/aifairness-isi.jpg\" alt=\"Robot holding balance scale\"\/><\/section>\n    <section><h2>AI Robustness and Safety<\/h2><p>Detecting and addressing performance disparities, enhancing robustness against adversarial inputs, measuring representation accuracy, analyzing information vectors and quality, predictive evaluation, and distributed assessment methodologies.<h3>People<\/h3><a href=\"http:\/\/isi.edu\/directory\/fredmors\/\" target=\"_blank\" rel=\"noopener\">Fred Morstatter<\/a> &#8211; <a href=\"https:\/\/www.isi.edu\/directory\/lerman\/\" target=\"_blank\" rel=\"noopener\">Kristina Lerman<\/a> &#8211; <a href=\"https:\/\/www.isi.edu\/directory\/jpujara\/\" target=\"_blank\" rel=\"noopener\">Jay Pujara<\/a> &#8211; Keith Burghardt<\/p><h3>Projects<\/h3><ul><li aria-level=\"1\"><strong>Evaluating AI System Robustness<\/strong><br \/>Many widely-used AI tools contain embedded representational skews. These projects focus on quantifying and assessing the downstream impacts of these calibration issues, including investigation of systematic failures in named entity recognition systems when processing different identifiers.<\/li><li aria-level=\"1\"><strong>Improving Data Representativeness<\/strong><br \/>Enhancing system robustness can be approached through model-agnostic methods, enabling the application of state-of-the-art models to appropriately balanced datasets. This project explores optimal methodologies for various data categories.<\/li><li aria-level=\"1\"><strong>Security Vulnerabilities in Calibration<\/strong><br \/>Strategic inputs can deliberately affect AI system behavior and output distributions. We investigate the effectiveness of such techniques in manipulating system robustness and develop safeguards to protect AI systems from these vulnerabilities.<\/li><\/ul><\/section>\n<\/article>\n","protected":false},"excerpt":{"rendered":"<p>The division conducts fundamental and applied research in the following topics: Areas of Research Machine Learning and Applications Natural Language Processing Knowledge Graphs Scientific Data Analysis and Discovery Multi-modal Understanding Common Sense Representation and Reasoning Computational Social Science AI Robustness and Safety Machine Learning and Applications Focusing on fundamental research, including AI robustness, adversarial machine&hellip;<\/p>\n","protected":false},"author":2,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"news_source":"","news_author":"","external_news_link":"","footnotes":""},"class_list":["post-8","page","type-page","status-publish","hentry"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v28.1 - 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